NSF: Fatigue, Damping and Impact Properties of Textile Composites

NSF:纺织复合材料的疲劳、阻尼和冲击性能

基本信息

  • 批准号:
    EP/C538129/1
  • 负责人:
  • 金额:
    $ 20.62万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2006
  • 资助国家:
    英国
  • 起止时间:
    2006 至 无数据
  • 项目状态:
    已结题

项目摘要

This project will study the fatigue, damping and impact properties of textile composites, as part of collaborative, interdisciplinary activities between six UK and US universities. Materials under consideration include thermoset 2D braids (carbon/glass hybrid with epoxy), thermoplastic 2D braids (carbon/aramid pre-impregnated with PA/TPU matrix), and 3D angle interlock weaves (also pre-impregnated thermoplastic tapes).Work at Cranfield will investigate experimentally damage initiation and fatigue properties of damaged composites under novel transient tests and damping properties of undamaged and damaged composites. Experimental optimization of composite parameters (braiding angle, plaque thickness, ratio of carbon/glass tows) for fatigue and damping properties will be undertaken.Experimental results will be compared with experimental results from both the UK and US partners.Predictive 3D unit cell FE models developed by the University of Nottingham and analytical and FE models developed by the US partner will be validated for novel transient tests by comparison with Cranfield experimental results.
该项目将研究纺织复合材料的疲劳、减震和冲击性能,作为英国和美国六所大学合作的跨学科活动的一部分。正在研究的材料包括热固性2D编织物(碳/玻璃与环氧树脂混杂)、热塑性2D编织物(预浸渍PA/TPU基质的碳/芳纶)和3D角度互锁编织(也包括预浸渍热塑性胶带)。克兰菲尔德的工作将在新的瞬变测试下研究受损复合材料的损伤起始和疲劳性能,以及未受损和受损复合材料的减振性能。将对复合材料的疲劳和减振性能参数(编织角、斑块厚度、碳/玻璃丝束比)进行实验优化。实验结果将与英国和美国合作伙伴的实验结果进行比较。诺丁汉大学开发的预测3D单胞有限元模型以及美国合作伙伴开发的分析和有限元模型将通过与克兰菲尔德实验结果的比较,在新的暂态测试中得到验证。

项目成果

期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Advanced Higher Order Spectra for Classification of Damage in Transient Conditions
用于瞬态条件下损坏分类的高级高阶光谱
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Len Gelman其他文献

A novel digital twin-enabled three-stage feature imputation framework for non-contact intelligent fault diagnosis
一种用于非接触式智能故障诊断的新型数字孪生使能的三阶段特征填补框架
  • DOI:
    10.1016/j.aei.2025.103434
  • 发表时间:
    2025-07-01
  • 期刊:
  • 影响因子:
    9.900
  • 作者:
    Yue Yu;Hamid Reza Karimi;Len Gelman;Xin Liu
  • 通讯作者:
    Xin Liu
A two-stage importance-aware subgraph convolutional network based on multi-source sensors for cross-domain fault diagnosis
  • DOI:
    10.1016/j.neunet.2024.106518
  • 发表时间:
    2024-11-01
  • 期刊:
  • 影响因子:
  • 作者:
    Yue Yu;Youqian He;Hamid Reza Karimi;Len Gelman;Ahmet Enis Cetin
  • 通讯作者:
    Ahmet Enis Cetin
Vibration health monitoring of rolling bearings under variable speed conditions by novel demodulation technique
通过新颖的解调技术监测变速条件下滚动轴承的振动健康状况
MSIFT: A novel end-to-end mechanical fault diagnosis framework under limited & imbalanced data using multi-source information fusion
MSIFT:一种利用多源信息融合在有限和不平衡数据下的新型端到端机械故障诊断框架
  • DOI:
    10.1016/j.eswa.2025.126947
  • 发表时间:
    2025-05-15
  • 期刊:
  • 影响因子:
    7.500
  • 作者:
    Yue Yu;Hamid Reza Karimi;Len Gelman;Ahmet Enis Cetin
  • 通讯作者:
    Ahmet Enis Cetin

Len Gelman的其他文献

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{{ truncateString('Len Gelman', 18)}}的其他基金

Assesment on on-wing engine health based on non linear dynamic engine behaviour
基于非线性动态发动机行为的在翼发动机健康评估
  • 批准号:
    EP/K504087/1
  • 财政年份:
    2013
  • 资助金额:
    $ 20.62万
  • 项目类别:
    Research Grant

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